{
"cells": [
{
"cell_type": "markdown",
"id": "4e50d971",
"metadata": {},
"source": [
"### One-bin A <-> 3B reaction, with 1st-order kinetics in both directions, taken to equilibrium\n",
"### Examine State Space trajectory, using [A] and [B] as state variables\n",
"\n",
"Based on experiment \"1D/reaction/reaction_2\"\n",
"\n",
"Diffusion not applicable (just 1 bin).\n",
"\n",
"This is the 1D version of the single-compartment reaction by the same name\n",
"\n",
"LAST REVISED: July 14, 2023"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "09b4fb67-3976-40c0-9e56-7060d243db7d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Added 'D:\\Docs\\- MY CODE\\BioSimulations\\life123-Win7' to sys.path\n"
]
}
],
"source": [
"import set_path # Importing this module will add the project's home directory to sys.path"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "e49a243f",
"metadata": {},
"outputs": [],
"source": [
"from experiments.get_notebook_info import get_notebook_basename\n",
"\n",
"from src.modules.chemicals.chem_data import ChemData\n",
"from src.life_1D.bio_sim_1d import BioSim1D\n",
"\n",
"import plotly.express as px\n",
"import plotly.graph_objects as go\n",
"from src.modules.visualization.graphic_log import GraphicLog"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "180bfbdd",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-> Output will be LOGGED into the file 'state_space_1.log.htm'\n"
]
}
],
"source": [
"# Initialize the HTML logging\n",
"log_file = get_notebook_basename() + \".log.htm\" # Use the notebook base filename for the log file\n",
"\n",
"# Set up the use of some specified graphic (Vue) components\n",
"GraphicLog.config(filename=log_file,\n",
" components=[\"vue_cytoscape_1\"],\n",
" extra_js=\"https://cdnjs.cloudflare.com/ajax/libs/cytoscape/3.21.2/cytoscape.umd.js\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "2bbdb53f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0:\n",
"1 bins and 2 species:\n",
" Species 0 (A). Diff rate: None. Conc: [10.]\n",
" Species 1 (B). Diff rate: None. Conc: [50.]\n"
]
}
],
"source": [
"# Initialize the system\n",
"chem_data = ChemData(names=[\"A\", \"B\"]) # NOTE: Diffusion not applicable (just 1 bin)\n",
"\n",
"\n",
"\n",
"# Reaction A <-> 3B , with 1st-order kinetics in both directions\n",
"chem_data.add_reaction(reactants=[\"A\"], products=[(3,\"B\")], forward_rate=5., reverse_rate=2.)\n",
"\n",
"bio = BioSim1D(n_bins=1, chem_data=chem_data)\n",
"\n",
"bio.set_uniform_concentration(species_index=0, conc=10.)\n",
"bio.set_uniform_concentration(species_index=1, conc=50.)\n",
"\n",
"bio.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "06fe0be5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of reactions: 1 (at temp. 25 C)\n",
"0: A <-> 3 B (kF = 5 / kR = 2 / Delta_G = -2,271.45 / K = 2.5) | 1st order in all reactants & products\n"
]
}
],
"source": [
"chem_data.describe_reactions()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "3f53fbc7",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" SYSTEM TIME | \n",
" A | \n",
" B | \n",
" caption | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" 0 | \n",
" 10.0 | \n",
" 50.0 | \n",
" | \n",
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\n",
" \n",
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\n",
"
"
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"text/plain": [
" SYSTEM TIME A B caption\n",
"0 0 10.0 50.0 "
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},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
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],
"source": [
"# Save the state of the concentrations of all species at bin 0\n",
"bio.add_snapshot(bio.bin_snapshot(bin_address = 0))\n",
"bio.get_history()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "4b5e75e5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[GRAPHIC ELEMENT SENT TO LOG FILE `state_space_1.log.htm`]\n"
]
}
],
"source": [
"# Send the plot to the HTML log file\n",
"graph_data = chem_data.prepare_graph_network()\n",
"GraphicLog.export_plot(graph_data, \"vue_cytoscape_1\")"
]
},
{
"cell_type": "markdown",
"id": "dfb4e9e3",
"metadata": {
"tags": []
},
"source": [
"### To equilibrium"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "b2500732",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0.5:\n",
"1 bins and 2 species:\n",
" Species 0 (A). Diff rate: None. Conc: [14.54390679]\n",
" Species 1 (B). Diff rate: None. Conc: [36.36827963]\n"
]
}
],
"source": [
"# Using smaller steps that in experiment reaction_2, to avoid the initial overshooting\n",
"bio.react(time_step=0.05, n_steps=10, snapshots={\"frequency\": 1, \"sample_bin\": 0})\n",
"bio.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "494466ba-f534-44c0-a65b-b4976340017a",
"metadata": {},
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\n",
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" 0.10 | \n",
" 13.625000 | \n",
" 39.125000 | \n",
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\n",
" \n",
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" 0.15 | \n",
" 14.131250 | \n",
" 37.606250 | \n",
" | \n",
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\n",
" \n",
" | 4 | \n",
" 0.20 | \n",
" 14.359063 | \n",
" 36.922812 | \n",
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\n",
" \n",
" | 5 | \n",
" 0.25 | \n",
" 14.461578 | \n",
" 36.615266 | \n",
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\n",
" \n",
" | 6 | \n",
" 0.30 | \n",
" 14.507710 | \n",
" 36.476870 | \n",
" | \n",
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\n",
" \n",
" | 7 | \n",
" 0.35 | \n",
" 14.528470 | \n",
" 36.414591 | \n",
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\n",
" \n",
" | 8 | \n",
" 0.40 | \n",
" 14.537811 | \n",
" 36.386566 | \n",
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\n",
" \n",
" | 9 | \n",
" 0.45 | \n",
" 14.542015 | \n",
" 36.373955 | \n",
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\n",
" \n",
" | 10 | \n",
" 0.50 | \n",
" 14.543907 | \n",
" 36.368280 | \n",
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\n",
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\n",
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" SYSTEM TIME A B caption\n",
"0 0.00 10.000000 50.000000 \n",
"1 0.05 12.500000 42.500000 \n",
"2 0.10 13.625000 39.125000 \n",
"3 0.15 14.131250 37.606250 \n",
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"6 0.30 14.507710 36.476870 \n",
"7 0.35 14.528470 36.414591 \n",
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"9 0.45 14.542015 36.373955 \n",
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"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
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"source": [
"bio.get_history()"
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},
{
"cell_type": "code",
"execution_count": 10,
"id": "d168a44c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A <-> 3 B\n",
"Final concentrations: [B] = 36.37 ; [A] = 14.54\n",
"1. Ratio of reactant/product concentrations, adjusted for reaction orders: 2.50059\n",
" Formula used: [B] / [A]\n",
"2. Ratio of forward/reverse reaction rates: 2.5\n",
"Discrepancy between the two values: 0.02341 %\n",
"Reaction IS in equilibrium (within 1% tolerance)\n",
"\n"
]
},
{
"data": {
"text/plain": [
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},
"execution_count": 10,
"metadata": {},
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],
"source": [
"# Verify that the reaction has reached equilibrium\n",
"bio.reaction_dynamics.is_in_equilibrium(rxn_index=0, conc=bio.bin_snapshot(bin_address = 0))"
]
},
{
"cell_type": "markdown",
"id": "3f5fd10b",
"metadata": {
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},
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"# Plots of changes of concentration with time"
]
},
{
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"execution_count": 11,
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df = bio.get_history()\n",
"\n",
"px.line(data_frame=df, x=\"SYSTEM TIME\", y=[\"A\", \"B\"], \n",
" title=\"Reaction A <-> 3B . Changes in [A] and [B] over time\",\n",
" color_discrete_sequence = ['navy', 'darkorange'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\"})"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c4e0120d-1541-4552-a2d0-8100a3fea8d9",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "e647f76c-4503-48be-b96a-22e81c9fadc5",
"metadata": {},
"source": [
"## Same data, but shown differently"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "85b3c06f",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
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],
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"fig0 = px.line(data_frame=bio.get_history(), x=\"A\", y=\"B\", \n",
" title=\"State space of reaction A <-> 3B : [A] vs. [B]\",\n",
" color_discrete_sequence = ['#C83778'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\"})\n",
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]
},
{
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"execution_count": 13,
"id": "50b08a83-7a05-4fa7-bbde-93d3d6402df9",
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AWMcDEIAABCAAAQhAAAIQgAAEIAABZQQI68oEoRwIQAACEIAABCAAAQhAAAIQgABhHQ9AAAIQgAAEIAABCEAAAhCAAASUESCsKxOEciAAAQhAAAIQgAAEIAABCEAAAoR1PAABCEAAAhCAAAQgAAEIQAACEFBGgLCuTBDKgQAEIAABCEAAAhCAAAQgAAEIENbxAAQgAAEIQAACEIAABCAAAQhAQBkBwroyQSgHAhCAAAQgAAEIQAACEIAABCBAWMcDEIAABCAAAQhAAAIQgAAEIAABZQQI68oEoRwIQAACEIAABCAAAQhAAAIQgABhHQ9AAAIQgAAEIAABCEAAAhCAAASUESCsKxOEciAAAQhAAAIQgAAEIAABCEAAAoR1PAABCEAAAhCAAAQgAAEIQAACEFBGgLCuTBDKgQAEIAABCEAAAhCAAAQgAAEIENbxAAQgAAEIQAACEIAABCAAAQhAQBkBwroyQSgHAhCAAAQgAAEIQAACEIAABCBAWMcDEIAABCAAAQhAAAIQgAAEIAABZQQI68oEoRwIQAACEIAABCAAAQhAAAIQgABhHQ9AAAIQgAAEIAABCEAAAhCAAASUESCsKxOEciAAAQhAAAIQgAAEIAABCEAAAoR1PAABCEAAAhCAAAQgAAEIQAACEFBGgLCuTBDKgQAEIAABCEAAAhCAAAQgAAEIENbxAAQgAAEIQAACEIAABCAAAQhAQBkBwroyQSgHAhCAAAQgAAEIQAACEIAABCBAWMcDEIAABCAAAQhAAAIQgAAEIAABZQQI68oEoRwIQAACEIAABCAAAQhAAAIQgABhHQ9AAAIQgAAEIAABCEAAAhCAAASUESCsKxOEciAAAQhAAAIQgAAEIAABCEAAAoR1PAABCEAAAhCAAAQgAAEIQAACEFBGgLCuTBDKgQAEIAABCEAAAhCAAAQgAAEIENbxAAQgAAEIQAACEIAABCAAAQhAQBkBwroyQSgHAhCAAAQgAAEIQAACEIAABCBAWMcDEIAABCAAAQhAAAIQgAAEIAABZQQI65aCNF/qtuwh/80rp06Uvv5Budo7mP/BGdEZAhVTJkj/4LBc7RlwpmYKzT8BfJJ/5i6OaHwyMDgsXbyfuChf3mrGJ3lD7fRA+MQt+ebPLHerYGXVEtYtBSGsWwKkuVoChDC10qgqDJ+okkNtMZxcq5VGVWH4RJUcaovBJ2qlSVoYYd1OL8K6HT8hrFsCpLlaAoQwtdKoKgyfqJJDbTGcXKuVRlVh+ESVHGqLwSdqpSGs50AawrolVMK6JUCaqyVACFMrjarC8IkqOdQWw8m1WmlUFYZPVMmhthh8olYawnoOpCGsW0IlrFsCpLlaAoQwtdKoKgyfqJJDbTGcXKuVRlVh+ESVHGqLwSdqpSGs50AawrolVMK6JUCaqyVACFMrjarC8IkqOdQWw8m1WmlUFYZPVMmhthh8olYawnoOpCGsW0IlrFsCpLlaAoQwtdKoKgyfqJJDbTGcXKuVRlVh+ESVHGqLwSdqpSGs50AawrolVMK6JUCaqyVACFMrjarC8IkqOdQWw8m1WmlUFYZPVMmhthh8olYawnoOpCGsi8h3n31BfvjTbaPw/uVjD8q9d97qfe/n296Ur3/nee/fd92+Rb711QelvGyi9zVhPQeupEsVBAhhKmRQXwQ+US+RigI5uVYhg/oi8Il6iVQUiE9UyOC7CB7d5htV0gMJ6x+GdUPnKw/fPwbSO3vq5JlnX5AfPPWIzKiY5gX7+GNdDOuNvaelTCbKgkmz7dxD61ATIISFWt7AJodPAkMZ6o44uQ61vIFNDp8EhjLUHeETt+QlrNvpRVhPE9ZNOF+6aO7IKntieHcprL/Vcli+X/eP0jnQ47lmTlmlPLXxSzKnbIadi2gdSgKEsFDKGvik8EngSEPZISfXoZQ18Enhk8CRhrJDfOKWrIR1O70I60kug49dAt/d0yfffPp52bJ5zUhYbzzRLF978jn59hMPSc2S+U5dBn/fjr+SrsEPgnrstWVmrXxj/R/YuYjWoSRACAulrIFPCp8EjjSUHXJyHUpZA58UPgkcaSg7xCduyUpYt9OLsJ7Az4Txhx97Rp584iFZV7vMC+v3feY2uWFjrXdkYljv7R+yUyCPrW/65X/wRpspZdIrg9Ip/TJv8gx56Xcfz2MVDOUKgdKSIhkeFhkcGnalZOosAAF8UgDo4wxpfl9Liot0FSUi+ESdJCoLwicqZVFXFD5RJ8m4BU2aUOxWwcqqJawnESR26fvWT21Ju7J+qaNPmaSpy7n91a95P7y7eLmcHr4i7w+flw0zquW71/9PzsyBQvNHYEpZiQwMifT2DeZvUEZyjgA+0SXZsAxLkegL68Yng0MiPbyf6DKMsmrwiTJBlJaDT5QKk6KsmdM/2JSbV3YECOvjhHWzG3yY7ln/i/1/J7su1Y0K6w/VbJXPLro5O/fQKtQEuLw51PIGNjl8EhjKUHfEZauhljewyeGTwFCGuiN84pa8XAZvp1fkw3pr+xXZ9toueeDeOzySiZe5h2k3+M6Bbnn17B4ZOHteukqHZMH8pXLH3OvsHETr0BIghIVW2kAnhk8CxRnazji5Dq20gU4MnwSKM7Sd4RO3pCWs2+kV+bAe20Tu5dd2jZD88fcfH7lH3XwzbM9Zbz5eJ1OmTZeKmfPt3EPrUBMghIVa3sAmh08CQxnqjji5DrW8gU0OnwSGMtQd4RO35CWs2+kV+bBuh0+c2g0+NlfCuq3q0WhPCIuGzrazxCe2BKPRnpPraOhsO0t8YkswGu3xiVs6E9bt9CKs2/EjrFvyo7leAoQwvdpoqgyfaFJDby2cXOvVRlNl+ESTGnprwSd6tUlWGWHdTi/Cuh0/wrolP5rrJUAI06uNpsrwiSY19NbCybVebTRVhk80qaG3FnyiVxvCevDaENYtmTZf6rbsIf/NuQw+/8xdHJEQ5qJq+a8Zn+SfuYsjcnLtomr5rxmf5J+5iyPiE7dUY2XdTi/Cuh0/VtYt+dFcLwFCmF5tNFWGTzSpobcWTq71aqOpMnyiSQ29teATvdqwsh68NoR1S6asrFsCpLlaAoQwtdKoKgyfqJJDbTGcXKuVRlVh+ESVHGqLwSdqpUlaGCvrdnoR1u34sbJuyY/megkQwvRqo6kyfKJJDb21cHKtVxtNleETTWrorQWf6NWGlfXgtSGsWzJlZd0SIM3VEiCEqZVGVWH4RJUcaovh5FqtNKoKwyeq5FBbDD5RKw0r6zmQhrBuCbVQYf1kw96sKx8YGJCioiIpKSnJuo/FKzZk3ZaGbhAghLmhU6GrxCeFVsCN8Tm5dkOnQleJTwqtgBvj4xM3dIpVyWXwdnoR1u34FewyeBPWsw3MlVMnSl//oFztHcxq9jZjZzUgjQpCgBBWEOzODYpPnJOsIAVzcl0Q7M4Nik+ck6wgBeOTgmDPelDCetbovIaEdTt+hHVLfjTXS4AQplcbTZXhE01q6K2Fk2u92miqDJ9oUkNvLfhErzbJKiOs2+lFWLfjR1i35EdzvQQIYXq10VQZPtGkht5aOLnWq42myvCJJjX01oJP9GpDWA9eG8K6JdNC3rPOZfCW4tF8XAKEMAzihwA+8UOJYzi5xgN+COATP5Q4Bp+45QFW1u30Iqzb8Sv4ynpHe5u8uv0luWPrPTK9otLXbE42HpRXtr/sHVs1a7bcdc/npaysfEzbuoN7Zcfrr4w5jnvWfWF2/iBCmPMS5mUC+CQvmJ0fhJNr5yXMywTwSV4wOz8IPnFLQsK6nV6EdTt+zoV1E+5/88ov5K7PfFYmlE+X7b98UaprVkrt2tG7uyd+CBB/HGHd0jSONCeEOSJUgcvEJwUWwJHhObl2RKgCl4lPCiyAI8PjE0eE+rBMwrqdXoR1O34FD+smRJ8+2TSy+v27v/f78t9//Qu53HJh1MzKJ0+Ruz/3gDSfPiGnjjfI79/7eW83eLN63tRYL1vvvm/U8Ynfj/+asG5pGkeaE8IcEarAZeKTAgvgyPCcXDsiVIHLxCcFFsCR4fGJI0IR1gMRirBuibHQ96xnehm8Cd2EdUvRI9KcEBYRoS2niU8sAUakOSfXERHacpr4xBJgRJrjE7eEZmXdTi/Cuh2/gq+sJ4b1np5uefmlv2dl3VJXmosQwnCBHwL4xA8ljuHkGg/4IYBP/FDiGHzilgcI63Z6Edbt+KkL6+mmM94962bV/d23/8W7XN684jeu4571dGTD93NCWPg0zcWM8EkuqIavT06uw6dpLmaET3JBNXx94hO3NCWs2+lFWLfjV/CwbsqP3bc+3s7u8dNMtRt8fFg3O8uzG7ylORxvTghzXMA8lY9P8gTa8WE4uXZcwDyVj0/yBNrxYfCJWwIS1u30Iqzb8VMR1jOdQuXUidLXP+htMJfNiw3msqHmXhtCmHuaFaJifFII6u6Nycm1e5oVomJ8Ugjq7o2JT9zSjLBupxdh3Y4fYd2SH831EiCE6dVGU2X4RJMaemvh5FqvNpoqwyea1NBbCz7Rq02yygjrdnoR1u34EdYt+dFcLwFCmF5tNFWGTzSpobcWTq71aqOpMnyiSQ29teATvdoQ1oPXhrBuybSQj26zLN2q+eIVG6za01g/AUKYfo00VIhPNKigvwZOrvVrpKFCfKJBBf014BP9GsVXyMq6nV6EdTt+BVtZtynb9p51m7Fp6w4BQpg7WhWyUnxSSPrujM3JtTtaFbJSfFJI+u6MjU/c0cpUSli304uwbsePsG7Jj+Z6CRDC9GqjqTJ8MlqNV8+9L02d52VKaZlUT50rH5u1WpNcBauFk+uCoXdqYHzilFwFKxafFAx9VgMT1rPCNtKIsG7Hj7BuyY/megkQwvRqo6kyfPKRGs8e3Sa/OL1rlDwP1WyVzy66WZNkBamFk+uCYHduUHzinGQFKRifFAR71oMS1rNG5zUkrNvxI6xb8qO5XgKEML3aaKoMn3ykxp1vfGOMNOsrl8p/3vigJskKUgsn1wXB7tyg+MQ5yQpSMD4pCPasByWsZ42OsG6H7oPWhdpgzqZ27lm3oRedtoSw6GhtM1N8MjasrymaKcMicnj4kkwpKZMXb/lzG8ShaMvJdShkzPkk8EnOEYdiAHziloyEdTu9WFm340dYt+RHc70ECGF6tdFUGT75SI37dvyVdA32eN94vGSLfH/wHdk4c4V8Y/0faJKsILVwcl0Q7M4Nik+ck6wgBeOTgmDPelDCetbovIaEdTt+hHVLfjTXS4AQplcbTZXhk4/UeKvlsHzv8D96gf3aomuktniW3LLxNqmZNk+TZAWphZPrgmB3blB84pxkBSkYnxQEe9aDEtazRkdYt0P3QWsugw+CIn1oJEAI06iKvprwyWhNzve0yrmeNu+bxU1nZdnytTJlWoU+4fJcESfXeQbu6HD4xFHh8lw2PskzcMvhCOt2AFlZt+NHWLfkR3O9BAhherXRVBk+Sa1G55U2Odl4RNZsvEmTZAWphZPrgmB3blB84pxkBSkYnxQEe9aDEtazRuc1JKzb8SOsW/KjuV4ChDC92miqDJ+Mr0bjkX1SOeMamTk72pfCc3Kt6bdWby34RK82mirDJ5rUSF8LYT09o/GOIKzH0enu6ZNvPv28951vffVBKS+b6P3759velK9/54Pv33X7llE/4zJ4OwPSWi8BQphebTRVhk/GV2Ogv0/2vfevct2WT2qSLe+1cHKdd+RODohPnJQt70Xjk7wjtxqQsG6Fj5X1GL5YUH/5tV2jAvk7e+rkmWdfkB889YjMqJgm3332Ba/JVx6+3/s/Yd3OgLTWS4AQplcbTZXhk/RqnDlxVKSoSBYsrkl/cEiP4OQ6pMIGPC18EjDQkHaHT9wSlrBupxcr6x/yMyF86aK53le73js0snoe+/69d97q/SwxvBPW7QxIa70ECGF6tdFUGT7xp8b7O38j195wi5SWTvDXIGRHcXIdMkFzNB18kiOwIesWn7glKGHdTi/Cusi1fdt5AAAgAElEQVSo1XJzyXssrBu05rL4LZvXSCysN55olq89+Zx8+4mHpGbJfFbW7fxHa8UECGGKxVFUGj7xJ0bLhWbpaL0ky1at99cgZEdxch0yQXM0HXySI7Ah6xafuCUoYd1Or8iHdRPOj586N3JZe7Kwft9nbpMbNtZ6pBPD+qWOXjsFCtB6SnmpDAwMSW//UAFGZ0hXCEwpK5WBoWHp7Rt0pWTqLACBKPukKEPeu9/dKctXrpZp0yszbOn/8KFhkeJMC/PffdZHTi4rlUHeT7Lm57fhsN8DlR5n3k+MT3r4u6NUIR1l4RMdOvitYub0SX4P5bgkBCIf1s1l7j/86bYxaMxGco//r38oT/2Xvx13Zd3FPygTSoplaHjY+4PICwKpCJSWFMnwsOATLDIugSj7JNN30La2Vjly6KDc9LGP58xVg4PDUlKiL61P+PD9xHwAyCt3BPQpn9lco/x+khmpaB+NT9zSv2xiiVsFK6s28mE9UY/4lXWzGzz3rCtzLOXkjQCXN+cNtdMD4ZPM5Ivqo9y4bDUzn6Q7unOgW/7u+Buys+WwnO9pk5tn1cofLPmk1Exz+xGB+CSd8vzcEMAnbvmAy+Dt9CKsJ/BLDOvsBm9nMFq7S4AQ5q52+awcn2RGe6C/X/a9t0Ou2/KpzBo6fjQn18EK+LfHX5e/O/76qE7nlFXKj7Z8JdiB8twbPskzcEeHwyduCUdYt9OLsJ4mrJsf85x1O5PR2k0ChDA3dct31fgkc+JRfJQbJ9eZ+2S8Fv9hz/Oyv+34mENe+PgTMrW0PNjB8tgbPskjbIeHwiduiUdYt9OLsG7Hj93gLfnRXC8BQphebTRVhk+yUyNqj3Lj5Do7n6RqFR/WHym5Xp4b3Cud0i8/2vKIzCmbEexgeewNn+QRtsND4RO3xCOs2+lFWLfjR1i35EdzvQQIYXq10VQZPslOjUsXzkpb60WpWXVtdh041oqT62AFi78M3mwq942S35EfTDggP97yaLAD5bk3fJJn4I4Oh0/cEo6wbqcXYd2OH2Hdkh/N9RIghOnVRlNl+CR7NQ7t2SWLa1bL1GkV2XfiSEtOroMVymww9+zR7bLrYp10DfbIjdNr5DP9i2XzTZ8MdqA894ZP8gzc0eHwiVvCEdbt9CKs2/EjrFvyo7leAoQwvdpoqgyfZK9G55U2Odl4RNZsvCn7Thxpycl17oW60tEqp5saZPWGG3M/WI5GCMIn53ta5XxPu1fhnLIKp28LyBFm57sNwifOQ3BoAoR1O7EI63b8COuW/GiulwAhTK82mirDJ3ZqROVRbpxc2/nEb+tLF89J26XzUlO7wW8TVcfZ+mRvW5N8+8BPpXOgZ2Re/8e6L8rHZq1WNU+KsSNg6xO70WmdKQHCeqbERh9PWLfjR1i35EdzvQQIYXq10VQZPhlfjZMNe8c9YGhoSNra2qSqqspa1sUr9AY0Tq6t5fXdwdnTx2Wgv1cWVa/y3UbLgbY+SbZLfhgeaadFHy112PpEyzyiUgdh3U5pwrodP8K6JT+a6yVACNOrjabK8En6sJ6PEG0+FMjHONl6j5PrbMll1+7EsTopm1QucxYsya6DArWy9cmdb3xjpPKbi+bLzuFm7+ttt/1F3mZkVvcv9rTJ7LIZcm3l0ryNG6WBbH0SJVYa5kpYt1OBsG7Hj7BuyY/megkQwvRqo6kyfEJY9+NHTq79UAr2mIbDe2TWNfNkxqw5wXacw95sffI/v/vX0tR5zqvwE0WLpLyoVHYUnZUXb/nzHFb9Udfx45vvLps6T/7v67+cl7GjNIitT6LESsNcCet2KhDW7fgR1i350VwvAUKYXm00VYZPCOt+/MjJtR9KwR/j2hMHbH3yj6d2ynON20dAbimaL78ztUZu33xH8HATenz13PvyvbqXxozj5575t1oOy/fr/nHkXvt7Ft4sf7p8q9eX2TBvZ0ud9++bZ9VKZ3+PTJ1QFumN82x9knMzMMAoAoR1O0MQ1u34EdYt+dFcLwFCmF5tNFWGTwjrfvzIybUfSrk5Zs/bb8iaTTfLxImTcjNAgL0G4RNzGfr+tuNeVcumzpVVQ5XScqFZVq3bHGClY7v62+Ovy98df937we8ULZC9wxekU/rlD5Z+Uv5waepH6pkw/qVd3xvT4SO198iU0nL5Twd+6v1sWESKZEiGhs3/i6SoyHy3SOaWzZD/6/p/J1NLy3M6P02dB+ETTfMJey2EdTuFCet2/AjrlvxorpcAIUyvNpoqwyf+w3rdwb2y4/VXvAZVs2bLXfd8XsrKxp5gpzpu547X5MDe90YGLJ88Re7+3AMyvaJSuGdd02+FrlqGh4fl3X99VW74+Kd1FZakmlyFsPbWFjl9vEHWbro5ZwziV9YnSLH87yXXy0tD9fKFtVvH3Y3efLjwxJ4fjanr9xdukX1tx0cu6x/20vqwyHAsqH/UZE3FIvk/Nz2Us7lp6zhXPtE2z7DUQ1i3U5KwbsePsG7Jj+Z6CRDC9GqjqTJ84i+sd7S3yavbX5I7tt7jhevtv3xRqmtWSu3a0Tu4j3ecCettrZdl6933jRmUsK7pt0JfLb093VK3/x3ZcMOt+oqLqyiXIayrs0MaDu2WjTd+IicMOge65Us7vyddgx89Nu7BCRvk+oXrZemSlSnHTBXWzYp8bKXeNP5s8Qr5h6EGKf6wp1VFVdI23CvnpUtKiorlV5/4jzmZl8ZOc+kTjfN1vSbCup2ChHU7foR1S34010uAEKZXG02V4RN/Yd2sljc11o8E7cSvY72Md1z8ynrphAle8F+4uNprSljX9Fuhs5YrHa1yuqlBVm+4UWeBIpLrENbX2yP73t0hm276pJSUlgbOwQT2V8/u8QL7lJIyuWPeRmk9fUr6erqlpjb5oxWThXxT2JMbvyTfq/u5XOhp9+rcUDRb/k1xtfxk8KCckU753eIlcmPRPNk7fFF+PdQkv7qNsB64oHQYCAHCuh1GwrodP8K6JT+a6yVACNOrjabK8En+wnr8SCbUH9y/e+RSesK6pt8KvbVcunhW2i5dlJraa1UWmeuwbiY9NDQku99+XdZuvFnKyifnhcOli+ek+eRR7zL84uKSMWOa1fVfnNrp3Wu/bNpc2TJztXx20c0Sf2m9uQp+spTKHxavlaPSKq8PnZTlRTPkC8W1UlRUJLWrr5MZM2fnZT6FHiQfPin0HMM0PmHdTk3Cuh0/wrolP5rrJUAI06uNpsrwSWHCeuLl8oR1Tb8Vums5e/q4DPT3yqLqVeoKzWcIMyvsy1aul6nTK/PCoftqlxzcvVNq11+f0ZiNV87Kzkt10jfUL139PbKz5bBsGKgScxn8T4YOSdWUCnl02q3S1dYqU6ZOl2W110pp6YS8zKlQg+TTJ4WaY5jGJazbqUlYt+NHWLfkR3O9BAhherXRVBk+8RfW092L3nzmlLdK3tfbm/Le9jd/82vZuHmLd887K+uafgvcq+VEY52UlZfLnPlLVBWf7xB2aO/bMm9hdV5XpM2Ys2bPl9nzFlmx77rSLvWHdsvCpSvkmjkLpKPtsjQc3iPDQ0OyaOkKmbNAl7ZWk01onG+fBFl7FPsirNupTli340dYt+RHc70ECGF6tdFUGT7xF9bNUePt8h4L62Z3+FTHmU3pTp9s8gaM3wnefM3KuqbfCjdqMcFu1jXzZMasOWoKLkQIM5vOVVZdI9fMXZg3DsePHvLGWrp8jfWYTfUHZHBwQJav3uj1ZT6Iudxyzltdr1l1rUyeOs16DG0dFMIn2hi4VA9h3U4twrodP8K6JT+a6yVACNOrjabK8In/sJ5L3QjruaQb3r4P7tklS2tWy5RpFSomWagQ1tRwUCaVlcv8RcvyxuHC2VPScr5Z1my8yXrMyy3n5Vj9flm55jqZXlklnR1t3iq7eRR71TVzZfGyWusxNHVQKJ9oYuBSLYR1O7UI63b8COuW/GiulwAhTK82mirDJ4R1P37k5NoPpcIcs+ftN2TNpptl4sRJhSkgbtRC+sQ8h31oaDCvwbbzSpvU7XtH1m76mHe1jM1raHBQ6g+97923HtuP4FRTvZhNBc3Ku7k/Pywb0BXSJzYaRbUtYd1OecK6HT/CuiU/muslQAjTq42myvAJYd2PHzm59kOpMMcMDw/Lu//6qtzw8U8XpgAlYd2Uce7MCbna2SHLVq3PGwuzO/3B3W/J/MU1MvOaedbjmg0EW86fkZVrr/OuFjDPlz96eK8UFxdJWfkUqV65zvkN6Hg/sbZJXjsgrNvhJqzb8SOsW/KjuV4ChDC92miqDJ+kD+v50mvxiuTPcc7X+OONw8m1BhVS19Db0y11+9+RDTfcWtBCNfik5UKzXLpwVlat25xXFo11+2TipDJZVL3Setzuq51Sf/B9mbtgqcyZv9jr78yJo3Lx/BkZHBiQhUuWO70BnQafWIsUoQ4I63ZiE9bt+BHWLfnRXC8BQphebTRVhk80qaG3Fk6u9WoTq+xKe6ucPtEgq6+9sWDFavFJe2uLmMvizXPR8/k6e7rJ29U9qA8KTjQelt6eq7Jy7QcfPJgQbz4UKCouFnNFxbIV65zcgE6LT/LpDZfHIqzbqUdYt+NHWLfkR3O9BAhherXRVBk+0aSG3lo4udarTXxl5v7mtksXpab22oIUrMkn5vJxs1P8xhs/kVcW5oOCY/UHZN2mm2VCAPsItF1ukYZD78uKNZu8Xe/Nq/nUMTnffEpKSkqksmpWXu/TDwKmJp8EMZ+w90FYt1OYsG7Hj7BuyY/megkQwvRqo6kyfKJJDb21cHKtV5vEysw9zwP9vSOblOWzcm0+6evtkX3v7pBNN31SSkpL84aiv69XDuzeKctWrpOKGbMCGddcFm8us489Ls6suMdW2bu7Or172V3ZgE6bTwIRKMSdENbtxCWs2/EjrFvyo7leAoQwvdpoqgyfaFJDby2cXOvVJlll5lndZeXlMmf+krwWrtEnZgO43W+/Lms33ixl5ZPzyuPIgfdkekWVzFtUHci45nFx5lJ784i38ilTvT7NpnpnTx3zNp8rnTDBiQ3oNPokEIFC2glh3U5YwrodP8K6JT+a6yVACNOrjabK8IkmNfTWwsm1Xm1SVdZwaI/MmjNPZsyck7fiNfvErLCbx59NnV6ZNx5moFPH66Wvp1tqaoPZQNJsJmge8TZr9nyZt/CDDwH6+nqlsc7sGF8iXVfaZcHiGtUb0Gn2SV7N4chghHU7odSE9e8++4L88KfbvNn85WMPyr13FnZHUr9Ymy91+z1UzXGVUydKX/+gXO0dVFMThegjQAjTp4nGivCJRlX01cTJtT5N/FR0cM8uWVqzWqZMq/BzuPUx2n1yaO/bXsDN9+Xily6ek+aTR70N70ygDuJlnsFugvmKtZukpOSDS/zNyrvZWG9axQzp7e1RuwGddp8EoU+Y+iCs26lZkLDeeKJZHn7sGTl7/pIXzBfNny073t4nX3n4funu6ZNvPv28bNm8xonATli3MyCt9RIghOnVRlNl+ESTGnpr4eRarzbpKtv99huBbXaWbiwXfGI2nTMbtV0zd2G66QT68+6rXXJw906pXX99YKv7He2XpeHgbqleuVaqZs316h0Y6PfuZS8uKpbevm7vMvzFy2oDnYttZy74xHaOYWpPWLdTM+9hPTGM/3zbm/L17zwvP/7+43LDxg/eDN7ZUycv/uoN+dZXH5Tysol2M8xxa8J6jgHTfcEIEMIKht6pgfGJU3IVrFhOrguGPuuBTzbs9dqaR3x1dXXJ1Kkf3OOc7WvxivSXcbvik6aGg1JWNjmwe8kzYWpW980l7LPnLcqk2bjHHj28V4pLir3L/GMv80x28+i3mdfMk9aW86o2oHPFJ4EJ5HhHhHU7AfMe1lvbr8gTf/WcfPXPviA1S+ZL4tdmOmbl/em//pk8+ecPyYyKaXYzzHFrwnqOAdN9wQgQwgqG3qmB8YlTchWsWE6uC4Y+64FNWPcTsP0M4Lcvl3xi7iUfHhoqyKrz8aOHPOyxnd39aJDumJbzzXKq6YisXHvdyG0PQ4OD0nhkn4gUmY9tvC7MrvGlpRPSdZfTn7vkk5yCcKRzwrqdUIR1O35sMGfJj+Z6CRDC9GqjqTJ8okkNvbVwcq1Xm1SV+Q3Yfmbmty/XfGJ2Ur/a2SHLVn20Iu2HRxDHmPvLTcBes/GmILrz+ujv7xPziLfKGbNkwZLlI/1eunhWjh3ZL3PnLxGz4l7oDehc80lgAjnaEWHdTjjCuh0/wrolP5rrJUAI06uNpsrwiSY19NbCybVebQjrdtq0XGiWSxfOyqp1m+06yqJ155U2qdv3jqzd9DEpnzwlix6SNzlzslHaLl/0VtknTPjgdlRzO4RZZR8eGpaJkybJlY62gm1Ax/tJYFLnpSPCuh1mwrodP8K6JT+a6yVACNOrjabK8IkmNfTWwsm1Xm0I6/batLe2eLuom93a8/0yz4E/uPstmb+4xru/PKiX2SnerLIvql4ps+YsGOm29dJ5bwO6eYuWifl3ITag4/0kKJXz0w9h3Y5zQcL6lx//nuw/fGzcytevXiY/eOoR7lm30zdpax7dlgOoIeySEBZCUXMwJXySA6gh7JKTa/dEjb90ve7gXtnx+iveJKpmzZa77vm8lJWVJ53U6ZNN8v47b8mn77p35JiwXgYfD6Crs0PMTvEbb/xEQcQ2AXripDIvXAf5OlZ/QIYGB2T56o2juj1Wv18G+vtk2vQqOXu6Ka8b0PF+EqTCue+LsG7HOO9h3a5cfa3ZYE6fJlQUDAFCWDAcw94LPgm7wsHMj5PrYDjms5dYwO5ob5NXt78kd2y9R6ZXVMr2X74o1TUrpXbt2N3dzc9MWE8M9FEI60abvt4e2ffuDtl00yelpPSDZ5fn82VCc0fb5cAvyb/ccl6a6vfLirXXeSvpsVfb5RZpPLJXFixeLlfaL3vfzscGdLyf5NNV9mMR1u0YEtZF5LvPviA//Om2EZLxj5Ez34w9Xs78+67bt4x6pBxh3c6AtNZLgBCmVxtNleETTWrorYWTa73apKosFrDNqnpTY71svfs+79DErxPbR3VlPcbBXJa+++3XZe3Gm6WsfHLehTeX5JvV8HWbbpYJEycFNv7g4KA0HHpfpkydLouqV43q93jDQenpueo9Uu7ksSM534CO95PAZM1LR4R1O8yRD+vm0XE/+tl2+fIf3eM90908Nu5rTz4n337iIe/RcuaZ7888+8LIJfkm2JvXVx6+3/s/Yd3OgLTWS4AQplcbTZXhE01q6K2Fk2u92hDWc6ONWWE3zy2fOr0yNwOM02t/X68c2L1Tlq1cJxUzZgU6/tnTx6Xl/Blv87lJcbdCmBV9swHd/EXV0tPTLVfaW3O2AR3vJ4FKmvPOCOt2iCMf1hPxmfBu7ql/9OH75YaNtd6q+9JFc+XeO2/1Dk0M74R1OwPSWi8BQphebTRVhk80qaG3Fk6u9WpDWM+dNof2vi3zF1ZL5czZuRtknJ6PHHjPu2x93qLqQMfvvtrpbT43b2G1zJ63aFTfJxrrpKuzXeYvWianTzTkZAM63k8ClTPnnRHW7RAT1hP4mTD+xJPPybPfeVTmz5kl33z6edmyec1IWE9ceSes2xmQ1noJEML0aqOpMnyiSQ29tXByrVebdGF9vHvWd+54TZrPnBq14VzUL4NP5Fl/aLfMqLpGrpm7sCAmOHW8Xvp6uqWmduweA7YFHT96yLtP36yyx786O9q8VXYT5IuKiqX5ZGOgG9DxfmKrXH7bE9bteBPWP+RnQvjDjz0jZ89fktg96909fV5Yv+8zt3mr7OaVGNb7B4bsFChA65LiIu95mUPDBRicIZ0h4PlERIYwijOaFaLQSPukqBDExx/T/E2aUFqsrrCSog/fT4b5w5NTcQLE+967v5XN19/olbtn927Ztu2fvH/PnjNHHnjgf5Dy8nJ59b+9IidOnhj5+mc//Ts5dqxxZIp33vlvZeOmTRLf13jzD+v7yb59e2TK5ClSs3xFTuVP1Xlz8xlpqD8iH7/lE1JSUhJoDRcunJd33/mtXH/DjTJ79pxRfdcdPiQtLRdl/fprpeFogxRJkVy7YaNMmDDBqoaw+sQKiuLGGv8mKcY1pjTCegKS+Mvg19UuS7uyfqGtxyW9vVqnTZ4g5oSup2/QudopOH8EppaXysDgMD7JH3InR4q0TwIMRkGJPyzD3gmxttfUyaUyODgs3b383cmpNgFKf6xujyyrHf24rmxr99uXeT/xfBLC85MTx+pleHhIltZ8sPiT71f31S7Z++5bsnbjDTItB/fRH97/nncP+7IVa0ZNretKh9Qf3uttPjdl6lQ5WndAFi1dLvMWLskaQZh9kjUUxQ1nV5Yprk5/aYT1JBrF36fOPev6TUyFuSHA5c254Rq2XvFJ2BTNzXy4bDU3XHPZq9/HrfmpwW9fYffJuTPH5WrnFVm2ar0fbDk5xtxHb4Jz4r3mQQx24ewp75nr5rL48slTR3V55sRRMY+Aq6m9Vi6eP2O1AV3YfRKEFpr64DJ4OzUiH9bNZe2v7XhP/vQPP+ORjF0O/+QTD3mXvrMbvJ3BaO0uAUKYu9rls3J8kk/a7o7FybV72vkN2H5m5revKPik5UKzXGm77N3DXaiXudfcvJYuH70KHkQ9vT3d3uZzs+YskHkLl47q0mxM11i3TyqrrpGqWXPkWMOBrDagi4JPgtBCSx+EdTslIh/WY/elv/zarhGSPGfdzlS0DgcBQlg4dMz1LPBJrgmHo39Ort3T0QTsIF+LV6Tf4CysPklk2dfXJxMnTgwS70hffjibg80qeMv5Zlmz8aac1HGq6Yh0dXbIijXXjblPvvnUMbl47oy3ym42o8t0A7qw+iQnQijolLBuJ0Lkw7odPp6zbsuP9noJEML0aqOpMnyiSQ29tXByrVcbTZWF1Sd+ryyw1SLTcTqvtEndvndk7aaPSfnkKbbDj2nf0X5ZGg6+711FUDVr7qif9/Zc9VbZzXPo5y+ukab6A97PzbGlpeNvQBdWnwQugJIOCet2QhDW7fgJj26zBEhztQQIYWqlUVUYPlElh9piOLlWK42qwsLqk0xDdLaiZDPO0NCQHNz9lheYZ14zL9uhx2139PBeKS4pkWVJLv0/d+aEnDvd5D1abmCg3wvtCxbXyJwFqTegC6tPcgJfQaeEdTsRCOt2/AjrlvxorpcAIUyvNpoqwyea1NBbCyfXerXRVFlYfZJNiM5GF5txzCr3xEllsqh6ZTZDp23Tcv6MnGqq9zafmzKtYtTxfX290li319uUztxHf+JY3bgb0IXVJ2khOnoAYd1OOMK6HT/CuiU/muslQAjTq42myvCJJjX01sLJtV5tNFUWVp/YhOhM9LEdx+zk3tF2WVat25zJsL6P7e/v8zafMxvMmdXzxJe5j/708QbvXvYJEyam3IAurD7xDdKxAwnrdoIR1u34EdYt+dFcLwFCmF5tNFWGTzSpobcWTq71aqOpsrD6JD5E1x3cKztef8XDXjVrttx1z+elrKw8qQynTzbJ+++8JZ++696RY3bueE0O7H1v5Hhzr/ndn3tApldUim1YN522t7bIsfoDsm7TzTJh4qSc2MM8xq2ttcVbZTehPP5lLoX3VvknTvLuXzeXySduQBdWn+QEtoJOCet2IhDW7fgR1i350VwvAUKYXm00VYZPNKmhtxZOrvVqo6mysPokFqI72tvk1e0vyR1b7/HC9fZfvijVNSuldu3YnfLNz0xYTwz0Jqy3tV6WrXffN0a6IMK66bS/r1cO7N7p3WNeMWNWTizSdaXdW2VfVL1KZs2ZP2YM8yz2E42HpWbVtTKtYsaoDehmVkyWgcFh6eoZyEltdBosAcK6HU/Cuh0/wrolP5rrJUAI06uNpsrwiSY19NYS1hCml7iblYXVJ7EQbVbVmxrrR4J24teJqqVbWS+dMMEL/gsXV3tNgwrrsTqOHHjPew76vEUf9J+L17H6/TI0OCTLV4/9wGJocFAaj+yT4uIS79L41ksXvNBes2KlzF+4lLCeC0Fy0Cdh3Q4qYd2OH2Hdkh/N9RIghOnVRlNl+ESTGnprCWsI00vczcrC6pMgw3q8sibsH9y/e+RS+qDDuhnr1PF66evp9nZrz9Xrcss5aao/KCvWbvI+HEh8Xbp4Vo4d2e+tslddM1fOnayX1suXZMnydTJ56rRclUW/AREgrNuBJKzb8SOsW/KjuV4ChDC92miqDJ9oUkNvLWENYXqJu1lZWH2Sq7CeeFl9LsK6cdKli+ek+eRRWbvpZm+VOxevwcEBaTi4W6ZMm+5dGp/4Gh4e9lbZh4eG5brNm6Wj44ocPLDHC/eLl9XmoiT6DIgAYd0OJGHdjh9h3ZIfzfUSIITp1UZTZfhEkxp6awlrCNNL3M3KwuoTP/esm3vRm8+cGrXhXLLL4N/8za9l4+Yt3j3v+VhZjzmp+2qXHNy9UzbddJuUlJbmzGBnTx+XlgtnZOWa62RSko33Wi+d9zagW7VmvUybMTfpBnQ5K46OsyJAWM8K20gjwrodP8K6JT+a6yVACNOrjabK8IkmNfTWEtYQppe4m5WF1Sd+doNPDOuxDeZiSt7yyX/jbUQX//34neDNcblaWY/VYPrv7++XCRMmBGKwxSuSX1rf3dUp9Yfel3kLq2X2vEVjxjI+2b93j/T09kjNqg0yLMOjNqArLQ2mvkAmSSdCWLczAWHdjh9h3ZIfzfUSIITp1UZTZfhEkxp6awlrCNNL3M3KwuqTXIfo+DCdKgAH4Ygg5+Gnr+NHD0lfb4/3iLf4V8wnZ5rPSeORvd5l87PnLhzZgM48w33OgiVBTJk+AiBAWLeDSFi340dYt+RHc70ECGF6tdFUGT7RpIbeWsIawvQSd7OysPrETzANQrFcjxNk/377art8URoO7ZYVazZJZdU1HqZEnxxvOIZWCtsAACAASURBVCg9PVe9DejMs+FPHKuTK+2tsmwFG9AF4SvbPgjrdgQJ63b8COuW/GiulwAhTK82mirDJ5rU0FtLWEOYXuJuVhZWn/gNpraq5XqcIPvPtC/zTHZzD/uSmtVjwrrh1tF22duAbv6iapkzf4lc7eyQYw0H2IDO1lQBtCes20EkrNvxI6xb8qO5XgKEML3aaKoMn2hSQ28tYQ1heom7WVlYfWKCab5eYboMPpHZ+eaTcu7Mcdl8/Y0yqXxq0uesn2isk67Odm+V3YT7c2dOSPPJRqleuU5mzJydLxkYJ44AYd3ODoR1O36EdUt+NNdLgBCmVxtNleETTWrorSWsIUwvcTcrwye6dfOzUV78DHp6uuXll/5eLrdc8L5dNWu29TPhe3u65ejh3TJv/kKpmrM4KbDOjjZvld1sTmc2qRsY6GcDugJai7BuB5+wbsePsG7Jj+Z6CRDC9GqjqTJ8okkNvbUQwvRqo6kyfKJJjbG1+HkEXXwr8xz4Pe/tkls/9XsSC+5r12/ydrXP9DL4+H6NT44cPiRt7W3eI96KS5I/+/1UU710tF2Smtprpax8ChvQFchehHU78IR1O36EdUt+NNdLgBCmVxtNleETTWrorYUQplcbTZXhE01qpA7r5vnuTY31svXu+7yDEr9ONQvz2LnqmpWBhPWBwWE5e/6CmHvZl61cL1Wz5iQdtquzw3su+8zZ88TsEm9ebECXX58R1u14E9bt+BHWLfnRXC8BQphebTRVhk80qaG3FkKYXm00VYZPNKkRbFhPDPS2K+smrHf1DHhFHj28R4pLSmXZynUpAZ45cVQut5z3VtknT5nGBnR5tBph3Q42Yd2OH2Hdkh/N9RIghOnVRlNl+ESTGnprIYTp1UZTZfhEkxrBhfWdO16TttbLIyvxpucgw7rpr+X8GTl1vEFWrtkkU6ZVJAXZfbXTW2U3j4BbuHSFdwwb0OXec4R1O8aEdTt+hHVLfjTXS4AQplcbTZXhE01q6K2FEKZXG02V4RNNaqQO6+Ze9Fe3vyR3bL1HpldUSvzl7SaYN5855W0kZ15mg7n5CxbJzbfcPqrDoMO66by/r1fqD+32wnjskvdkRJtPHZOL5854q+xTp1WwAV2ObUdYtwNMWLfjR1i35EdzvQQIYXq10VQZPtGkht5aCGF6tdFUGT7RpEbqsG5+Yi5r3/H6K95B8bu8x4f1lgvnvFA/0N8/0tnCxdXeCnsuwnpsEHPJe3tri6xYe51MmDAxKdTenqveKvvU6ZWyeFmtd0zrpQvervEm6M9ZsES3GA5VR1i3E4uwbsePsG7Jj+Z6CRDC9GqjqTJ8okkNvbUQwvRqo6kyfKJJjfHDum2luQzrprbOK+3ScPB9WVS9SmbNmZ+yXHMZ/LnTTVJTu0GmVczwjmMDOlt1R7cnrNvxJKzb8SOsW/KjuV4ChDC92miqDJ9oUkNvLYQwvdpoqgyfaFLD7bAeq/5Y/X4ZGhqS5bUbUsLt6+uVxrq9Uj55qixdvsY77mpnhxxrOCDTK6pGVt51q6O3OsK6nTaEdTt+hHVLfjTXS4AQplcbTZXhE01q6K2FEKZXG02V4RNNaoQjrJtZXL54TpoaDsrKtdeNrJ4nI33h7Ck5fbzBu5e9YsYs7xA2oLP3JGHdjiFh3Y4fYd2SH831EiCE6dVGU2X4RJMaemshhOnVRlNl+ESTGsnDepAVLl6RerV7vHGy8cng4ID3TPap0yplUfXKlN0PDPR797JPnDhJqj98FJz5nrmX3bzM90pLJwSJIfR9EdbtJCas2/EjrFvyo7leAoQwvdpoqgyfaFJDby3ZnFzrnQ2V5YoAPskV2XD1a+OTs6ebpOVCs6xcc51MKitPCebi+TNyovGw1Ky6VmbMnO0dxwZ02fmIsJ4dt1grwrodP8K6JT+a6yVACNOrjabK8IkmNfTWYnNyrXdWVBY0AXwSNNFw9mfrk+6uTqk/9L7MW1gts+ctSglpaHBQGo/sk+LiEu/S+NiLDegy8xVhPTNeiUcT1u34EdYt+dFcLwFCmF5tNFWGTzSpobcW25NrvTOjsiAJ4JMgaYa3r6B8cvzoIem92iHl5alX2A3Fnp4eaW9vl4qKCikrK/PA9vf3S0dHh0ycOFGmTZs2AjvbS/vDq5YIYd1OXcK6HT/CuiU/muslQAjTq42myvCJJjX01hLUybXeGVJZEATwSRAUw99HkD45dvg9WbZ6c1pow8PD3ir78NCwt8peXFzstYnfgO7K5bNCWB+LkrCe1l7jHkBYt+NHWLfkR3O9BAhherXRVBk+0aSG3lqCPLnWO0sqsyWAT2wJRqN9kD7J9HnvrZfOexvQLV2+duT57bEN6Lq7OmTNpo+xAV2CDQnrdr+XhHU7foR1S34010uAEKZXG02V4RNNauitJciTa72zpDJbAvjElmA02gfpk0zDeoyweX77QH+f1KzaICWlpd636/e/LZ2dXbJgcY3MWbAkGmL4mCVh3QekcQ4hrNvxI6xb8qO5XgKEML3aaKoMn2hSQ28tQZ5c650lldkSwCe2BKPRPkifZBvWDem2yy3SeGSvLKpeJbPnLpRYX2xAN9qHhHW730vCuh0/wrolP5rrJUAI06uNpsrwiSY19NYS5Mm13llSmS0BfGJLMBrtg/RJfFivO7hXdrz+igexatZsueuez0tZwuPdenq65eWX/l4ut1wYOW7DxutkoL9XyiaWytJVm7zvX+3skGMNB2R6RZUsXlYbDWFSzJKwbid/5MN6d0+ffPPp5+Xl13aNkPzx9x+XGzZ+9Iv1821vyte/87z387tu3yLf+uqDUl420fu6+VK3nQIFaF05daL09Q/K1d7BAozOkK4QIIS5olRh68QnheXvyuhBnly7MmfqzJwAPsmcWRRbBOmTWFjvaG+TV7e/JHdsvUemV1TK9l++KNU1K6V27YZRiM1xe97bJbd+6ve875vjKmdUydr1m6T+4HuyqHqlzJn/0SXw8RvQxZ7XHjXNCOt2ikc+rLe2X5Ef/Wy7fPmP7vEC+Dt76uSJJ5+TZ7/zqNQsme99/cyzL8gPnnpEZlRMk+8++4JH/CsP309Yt/MerZUTIIQpF0hJefhEiRDKywjy5Fr5VCnPggA+sYAXoaZB+iQW1s2qelNjvWy9+z6PZOLXyfDGVtlNUDeh3vQ1XDxJujrbpWbVtTLpw1X52AZ0po/qlesitwEdYd3ulzPyYT0RnwnvX378e/Low/d7q+smnC9dNFfuvfNW79DE8M7Kup0Baa2XACFMrzaaKsMnmtTQW0uQJ9d6Z0lltgTwiS3BaLQP0ifZhvWdO16TA3vfk3UbNsvNt9zugY/11dnR5j3mbfa8RTJvYfWIKK2XLkhT/YHIbUBHWLf7vSSsJ/BrPNEsX3vyOfn2Ew/J/DmzvEvkt2xeMxLW439uVt4J63YGpLVeAoQwvdpoqgyfaFJDby1BnlzrnSWV2RLAJ7YEo9E+SJ9kG9ZjpE1oNy8T2BM3qzvVVC8dbZe857KXlU8ZESdqG9AR1u1+Lwnrcfxi96/Hwnns6/s+c9vIPeyJYb2ts99OgQK0nlxWIgODw9LXP1SA0RnSFQLlk0pkcAifuKJXoerEJ4Uin3zcYRmWIinSVZSIGJ8MDQ1LL3931GmjqSB8okkNvbUE6ZO6A+9J7brN0t7WKv/0y3+Qf3v356Sicoa89A8/k+Ura2Xd+o3yz6+/KqdPnZDP3feAnD9/Vs42n5EtH7vFA2R+Zl6f+OQdEusrntyVK+1yeP9umT1vgSytXjHyo84rHVJ3aK9Uzpgpy1eu0Qs7gMoqp04IoJfodkFY/1D7WDCfO7tq5H70xPBuDk0M61d7B5xzz8RSc9I0JANDw87VTsH5IzCxtFiMRQYG+VAnf9TdGwmf6NJsaEikuFhXTaYafKJPE40V4RONquirKUif7Nv9rly76Xpvkvv27pZXtm/z/n3N7Dny+S8+IOXl5fKb//7f5OTJk97Xvb098pP/72/kalfXmOPi+0qkdrThiFw4d07Wb9wk06ZNH/nxieNNcuxovaxdv0Fmz5mrD3YAFU2e9MFz6HllR4CwLiLJgnoMJ/esZ2csWrlPgMub3dcwHzPAJ/mg7P4YQV626j4NZpCKAD7BG34IBOkTm+esJ9aarq/uq53SWLdPKquukYVLP1plD/sGdFwG78fVqY+JfFhPtnoej4vd4O0MRmt3CRDC3NUun5Xjk3zSdnesIE+u3aVA5ekI4JN0hPi5IRCkT9IF7EyI++2r+dQxuXjujHcv+9RpFSNDhHUDOsJ6Ji4ae2zkw7q5rP3hx56Rs+cvjaLzJ1+8c+RyeJ6zbmcyWrtJgBDmpm75rhqf5Ju4m+MFeXLtJgGq9kMAn/ihxDFB+sRvwPZDPZO+enuueqvsU6dXyuJltaO6D9sGdIR1P+5JfUzkw7odPmE3eFuAtFdLgBCmVhpVheETVXKoLSbIk2u1k6QwawL4xBphJDoI0icmYAf5WrxiQ0bdnTtzQs6dbpKa2g0yrWLGSNurnR1yrOGATK+oGhPmMxpAwcGEdTsRCOt2/AjrlvxorpcAIUyvNpoqwyea1NBbS5An13pnSWW2BPCJLcFotA+bT/r6eqWxbq+UT54qxcOjnzLV1dUl5r/p06dLWVlZVgJn+gFCVoOM04iwbkeUsG7Hj7BuyY/megkQwvRqo6kyfKJJDb21hO3kWi9ptyvDJ27rl6/qw+qTC2dPSWfbBVm2evMolDYb0GVyaX6u9COs25ElrNvxI6xb8qO5XgKEML3aaKoMn2hSQ28tYT251kvczcrwiZu65bvqMPvkRP0eWbJyY1Kk2WxAR1jPtzuDH4+wbsm0+VK3ZQ/5b145daL09Q/K1d7B/A/OiM4QIIQ5I1VBC8UnBcXvzOBhPrl2RgQHCsUnDoikoMQw+8RPuM5kAzo//eVaUlbW7QgT1u34sbJuyY/megkQwvRqo6kyfKJJDb21hPnkWi919yrDJ+5pVoiKw+wTv+Ha7wZ0fvvLpY6EdTu6hHU7foR1S34010uAEKZXG02V4RNNauitJcwn13qpu1cZPnFPs0JUHGafxIfruoN7Zcfrr3iIq2bNlrvu+byUlZWPQm52k28+2SjVK9fJrn/9Z7l6tWvUcYT1Qjg02DEJ65Y8uQzeEiDN1RIghKmVRlVh+ESVHGqLCfPJtVroDhaGTxwUrQAlh9knsXDd0d4mr25/Se7Yeo9Mr6iU7b98UaprVkrt2rGPhjMb0L2383Xp6uqUrqs9csednx0J9YT1Ahg04CEJ65ZACeuWAGmulgAhTK00qgrDJ6rkUFtMmE+u1UJ3sDB84qBoBSg5zD6JhWuzqt7UWC9b777PI5z4dTx287OD+3fL2nUbpP3yeVmwZLksXLLcO4SwXgCDBjwkYd0SKGHdEiDN1RIghKmVRlVh+ESVHGqLCfPJtVroDhaGTxwUrQAlh9knmYZ1E9Tffftf5O7PPSAd7a3y/jtvybr1G+Rq1xVZtmKdtJw9JjxnvQAmDXBIwrolTMK6JUCaqyVACFMrjarC8IkqOdQWE+aTa7XQHSwMnzgoWgFKDrNPMg3r5vL40yebRqlg7m//1KfvkjMnGqRoeEjWXvfxAqj00ZBsMGeHn7Bux48N5iz50VwvAUKYXm00VYZPNKmht5Ywn1zrpe5eZfjEPc0KUXGYfeLnnvWdO16T5jOnxmw4Z0K7WVn/9F33jtyzfnjPW9Ld3eNtQDdj5uxCyCWEdTvshHU7foR1S34010uAEKZXG02V4RNNauitJcwn13qpu1cZPnFPs0JUHGaf+NkNPpOwbvqbX71GmuoPeFKZ0F5aOiGvshHW7XAT1u34EdYt+dFcLwFCmF5tNFWGTzSpobeWMJ9c66XuXmX4xD3NClFxmH0S9IZw8f21XrrghfYFi2tkzoIleZOOsG6HmrBux4+wbsmP5noJEML0aqOpMnyiSQ29tYT55FovdfcqwyfuaVaIisPsk1yG9ZhWJ47VyZX2Vm8DuslTp+VcQsK6HWLCuh0/wrolP5rrJUAI06uNpsrwiSY19NYS5pNrvdTdqwyfuKdZISoOs0/yEdaNZlc7O+RYwwGZXlEli5fV5lRGwrodXsK6HT/CuiU/muslQAjTq42myvCJJjX01hLmk2u91N2rDJ+4p1khKg6zT0xYD/o13qPbzp05Ic0nG3O6AR1h3U5RwrodP8K6JT+a6yVACNOrjabK8IkmNfTWEuaTa73U3asMn7inWSEqxifBUh8Y6B+1AV1z06FAB9iyZUug/UWtM8K6peI8Z90SIM3VEiCEqZVGVWH4RJUcaovh5FqtNKoKwyeq5FBbDD7JjTSxDegqKqZLzZrrAxnEXClAWLdDSVi348fKuiU/muslQAjTq42myvCJJjX01sLJtV5tNFWGTzSpobcWfJJbbRoO/FZWrLsxkEEI6/YYCeuWDFlZtwRIc7UECGFqpVFVGD5RJYfaYji5ViuNqsLwiSo51BaDT3IrTZCb3BHW7bUirFsyJKxbAqS5WgKEMLXSqCoMn6iSQ20xnFyrlUZVYfhElRxqi8EnuZWGsJ5bvpn2TljPlFjC8YR1S4A0V0uAEKZWGlWF4RNVcqgthpNrtdKoKgyfqJJDbTH4JLfSxIf1uoN7Zcfrr3gDVs2aLXfd83kpKysfVUBPT7e8/NLfy+WWCyPfX7i4WrbefZ+wsm6vFWHdkiFh3RIgzdUSIISplUZVYfhElRxqi+HkWq00qgrDJ6rkUFsMPsmtNLGw3tHeJq9uf0nu2HqPTK+olO2/fFGqa1ZK7doNScP62vWbxvyMsG6vFWHdkiFh3RIgzdUSIISplUZVYfhElRxqi+HkWq00qgrDJ6rkUFsMPsmtNLGwblbVmxrrvRVy80r8OlZF4sp6/Ao8Yd1eK8K6JUPCuiVAmqslQAhTK42qwvCJKjnUFsPJtVppVBWGT1TJobYYfJJbaTIN64nVmBX4yhlVcvMtt3MZfABSEdYtIRLWLQHSXC0BQphaaVQVhk9UyaG2GE6u1UqjqjB8okoOtcXgk9xKYxvW41fgWVm314qwbsmQsG4JkOZqCRDC1EqjqjB8okoOtcVwcq1WGlWF4RNVcqgtBp/kVho/96zv3PGaNJ855W0419fbK3ve2yW3fur3vMJYWQ9WH8K6JU/CuiVAmqslQAhTK42qwvCJKjnUFsPJtVppVBWGT1TJobYYfJJbafzsBp8Y1n/5Dz+R7qtdXmGxneDNv1lZt9eKsG7JkLBuCZDmagkQwtRKo6owfKJKDrXFcHKtVhpVheETVXKoLQaf5FYanrOeW76Z9k5Yz5RYwvGEdUuANFdLgBCmVhpVheETVXKoLYaTa7XSqCoMn6iSQ20x+CS30hDWc8s3094J65kSI6xbEqO5KwQIYa4oVdg68Ulh+bsyOifXrihV2DrxSWH5uzI6PsmtUoT13PLNtHfCeqbECOuWxGjuCgFCmCtKFbZOfFJY/q6Mzsm1K0oVtk58Ulj+royOT3KrlAnrQb62bNkSZHeR64uwHjnJmTAEIAABCEAAAhCAAAQgAAEIaCdAWNeuEPVBAAIQgAAEIAABCEAAAhCAQOQIENYjJzkThgAEIAABCEAAAhCAAAQgAAHtBAjr2hWiPghAAAIQgAAEIAABCEAAAhCIHAHCegQkbzzRLE//9c/kyT9/SGZUTBuZcXdPn3zz6efl5dd2ed/7y8celHvvvDUCRJhiMgKpfBI79ufb3pTjp87JVx6+H4ARJpDKJ9999gX54U+3jZDh/STCJhGRVD4x7yNf/87z+CTa9hiZfbq/O+ZA897y2z118oOnHhl1DgPC6BDw+35iiPzJF+/kPCU61ojETAnrIZa5tf2KfPnx78n+w8dk/eplY/7QmT+A5mXCV+zYRx++X27YWBtiKkwtkUA6n7yzp07++N8/5TXjj2B0/TOeT8wHfz/4m5fkS1/Y6p1MmxOrhx97Rp584iHeTyJmmUx8wt+diJkjbrrp/u7EDo19CJjsHCa69KIz83Q+MR/+7XrvkHzrqw9KednE6IBhppEiQFiPgNzJPpE0b4BP/NVz8tU/+4LULJnvUYgP7xHAwhQTCKRb4WBlHcsYAul8Yo6JXbWzZfMartaJqG3wSUSFz3Da4/kk9jfnlpuulWeefYGV9QzZhunw8VbWCethUpq5JCNAWI+AL5K9yZnvfe3J5+TbTzw0Etb5hDICZhhniulOrgnr0fZHbPbpfGKOY8UUr/jxCVdg4BM/IexA3THCesSt4vcyeK7+i7hRQjp9wnpIhY2fVqqwnngfO2E9AmYgrEdb5ABm7yeEcZVOAKAd72I8n8Rf2sreBo4LbVl+Mp+YW69e/NUbI5c2m69ZWbcE7XhzP393Yu8r93/mNq7oclxvyh9NgLAeAUewsh4BkQOYYro/hqysBwA5BF2k84kJ6ucuXOYewhBobTOFdD4xfXO7hA3hcLRN5pPETQhjM+W+9XBons0s/LyfmH45T8mGLm20EyCsa1cogPq4Zz0AiBHoIt0fQ/4IRsAEPqY4nk8I6j4ARuSQdO8nMQy8r0TEECmm6ccnrKxH2yNm9n58QljHJ2ElQFgPq7Jx80r1Jsdu8BEQP4MppvtjyEl1BjBDfKif95MQT5+p+SSQ6kPiH/1su3z5j+7xdm7mslWfMEN8WLq/O2bqhPUQG8Dn1JL5xFyZ8w8v/7N87q5PjHo/4alGPqFymDMECOvOSJV5ofH3BcZax2++wXPWM2caxhbpfBL/6LbY/H/8/cd5JFcYzTDOnMbzSbKfma7uun0Ll8Pjk1GPfIw9iiuGhXvWI2aQD6eb7u9OPBXCejQ9Ymadzie8n0TXG1GaOWE9SmozVwhAAAIQgAAEIAABCEAAAhBwggBh3QmZKBICEIAABCAAAQhAAAIQgAAEokSAsB4ltZkrBCAAAQhAAAIQgAAEIAABCDhBgLDuhEwUCQEIQAACEIAABCAAAQhAAAJRIkBYj5LazBUCEIAABCAAAQhAAAIQgAAEnCBAWHdCJoqEAAQgAAEIQAACEIAABCAAgSgRIKxHSW3mCgEIQAACEIAABCAAAQhAAAJOECCsOyETRUIAAhCAAAQgAAEIQAACEIBAlAgQ1qOkNnOFAAQgAAEIQAACEIAABCAAAScIENadkIkiIQABCEAAAhCAAAQgAAEIQCBKBAjrUVKbuUIAAhCAAAQgAAEIQAACEICAEwQI607IRJEQgAAEIAABCEAAAhCAAAQgECUChPUoqc1cIQABCEAAAhCAAAQgAAEIQMAJAoR1J2SiSAhAAAIQgAAEIAABCEAAAhCIEgHCepTUZq4QgAAEIAABCEAAAhCAAAQg4AQBwroTMlEkBCAAAQhAAAIQgAAEIAABCESJAGE9SmozVwhAAAIQgAAEIAABCEAAAhBwggBh3QmZKBICEIAABCAAAQhAAAIQgAAEokSAsB4ltZkrBCAAAQiElsDPt70pX//O8/InX7xTvvLw/aGdJxODAAQgAAEIRIUAYT0qSjNPCEAAAhAILYHunj755tPPS/uVLu+/Hzz1iMyomBba+TIxCEAAAhCAQBQIENajoDJzhAAEIACBUBNoPNEsX3vyOXn0331ennn2Bbn/M7fJvXfeGuo5MzkIQAACEIBA2AkQ1sOuMPODAAQgAIHQEzCXwB8/dc67/P27z74g5y5clm999UEpL5sY+rkzQQhAAAIQgEBYCRDWw6os84IABCAAgUgQaG2/Il9+/Hvy6MP3yw0bayW2yv7tJx6SmiXzI8GASUIAAhCAAATCSICwHkZVmRMEIAABCESGwDt76rxL32P3qcfuX9+yeQ2XwkfGBUwUAhCAAATCSICwHkZVmRMEIAABCESGgLns/Yc/3TZmvutXL2Ojuci4gIlCAAIQgEAYCRDWw6gqc4IABCAAgUgQSLwEPjZpcyn8w489I08+8ZB3aTwvCEAAAhCAAATcI0BYd08zKoYABCAAAQh4BMzGci/86o0xK+ixS+Hnzq7imet4BQIQgAAEIOAoAcK6o8JRNgQgAAEIRJtAukCeKshHmxqzhwAEIAABCLhDgLDujlZUCgEIQAACEIAABCAAAQhAAAIRIUBYj4jQTBMCEIAABCAAAQhAAAIQgAAE3CFAWHdHKyqFAAQgAAEIQAACEIAABCAAgYgQIKxHRGimCQEIQAACEIAABCAAAQhAAALuECCsu6MVlUIAAhCAAAQgAAEIQAACEIBARAgQ1iMiNNOEAAQgAAEIQAACEIAABCAAAXcIENbd0YpKIQABCEAAAhCAAAQgAAEIQCAiBAjrERGaaUIAAhCAAAQgAAEIQAACEICAOwQI6+5oRaUQgAAEIAABCEAAAhCAAAQgEBEChPWICM00IQABCEAAAhCAAAQgAAEIQMAdAoR1d7SiUghAAAIQgAAEIAABCEAAAhCICAHCekSEZpoQgAAEIAABCEAAAhCAAAQg4A4Bwro7WlEpBCAAAQhAAAIQgAAEIAABCESEAGE9IkIzTQhAAAIQgAAEIAABCEAAAhBwhwBh3R2tqBQCEIAABCAAAQhAAAIQgAAEIkKAsB4RoZkmBCAAAQhAAAIQgAAEIAABCLhDgLDujlZUCgEIQAACEIAABCAAAQhAAAIRIUBYj4jQTBMCEIAABCAAAQhAAAIQgAAE3CFAWHdHKyqFAAQgAAEIQAACEIAABCAAgYgQIKxHRGimCQEIQAACEIAABCAAAQhAAALuECCsu6MVlUIAAhCAAAQgAAEIQAACEIBARAgQ1iMiNNOEAAQgAAEIQAACEIAABCAAAXcIENbd0YpKIQABCEAAAhCAAAQgAAEIQCAiBAjrERGaaUIAAhCAAAQgAAEIQAACEICAOwQI6+5oRaUQgAAEIAABCEAAAhCAAAQgEBEChPWICM00IQABCEAAAhCAAAQgPWoxnwAAAVFJREFUAAEIQMAdAoR1d7SiUghAAAIQgAAEIAABCEAAAhCICAHCekSEZpoQgAAEIAABCEAAAhCAAAQg4A4Bwro7WlEpBCAAAQhAAAIQgAAEIAABCESEAGE9IkIzTQhAAAIQgAAEIAABCEAAAhBwhwBh3R2tqBQCEIAABCAAAQhAAAIQgAAEIkKAsB4RoZkmBCAAAQhAAAIQgAAEIAABCLhDgLDujlZUCgEIQAACEIAABCAAAQhAAAIRIUBYj4jQTBMCEIAABCAAAQhAAAIQgAAE3CFAWHdHKyqFAAQgAAEIQAACEIAABCAAgYgQIKxHRGimCQEIQAACEIAABCAAAQhAAALuECCsu6MVlUIAAhCAAAQgAAEIQAACEIBARAgQ1iMiNNOEAAQgAAEIQAACEIAABCAAAXcIENbd0YpKIQABCEAAAhCAAAQgAAEIQCAiBP5/9lsImLkCcF8AAAAASUVORK5CYII=",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Now show the individual data points\n",
"\n",
"df['SYSTEM TIME'] = round(df['SYSTEM TIME'], 2) # To avoid clutter from too many digits, in the column\n",
"\n",
"fig1 = px.scatter(data_frame=df, x=\"A\", y=\"B\",\n",
" title=\"Trajectory in State space: [A] vs. [B]\",\n",
" hover_data=['SYSTEM TIME'])\n",
"\n",
"fig1.update_traces(marker={\"size\": 6, \"color\": \"#2FAC74\"}) # Modify the style of the dots\n",
"\n",
"# Add annotations (showing the System Time value) to SOME of the points, to avoid clutter\n",
"for ind in df.index:\n",
" label = df[\"SYSTEM TIME\"][ind]\n",
" if ind == 0:\n",
" label = f\"t={label}\"\n",
" \n",
" label_x = ind*16\n",
" label_y = 20 + ind*8 # A greater y value here means further DOWN!!\n",
" \n",
" if (ind <= 3) or (ind%2 == 0):\n",
" fig1.add_annotation(x=df[\"A\"][ind], y=df[\"B\"][ind],\n",
" text=label,\n",
" font=dict(\n",
" size=10,\n",
" color=\"grey\"\n",
" ),\n",
" showarrow=True, arrowhead=0, ax=label_x, ay=label_y, arrowcolor=\"#b0b0b0\",\n",
" bordercolor=\"#c7c7c7\")\n",
"\n",
"fig1.show()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "f3c287ce-9a33-43bd-8473-f81f22ff9e81",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"hovertemplate": "A=%{x}
B=%{y}",
"legendgroup": "",
"line": {
"color": "#C83778",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "",
"orientation": "v",
"showlegend": false,
"type": "scatter",
"x": [
10,
12.5,
13.625,
14.13125,
14.3590625,
14.461578125,
14.50771015625,
14.5284695703125,
14.537811306640625,
14.54201508798828,
14.543906789594727
],
"xaxis": "x",
"y": [
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42.5,
39.125,
37.60625,
36.9228125,
36.615265625,
36.47686953125,
36.4145912890625,
36.386566080078126,
36.37395473603516,
36.36827963121582
],
"yaxis": "y"
},
{
"customdata": [
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0
],
[
0.05
],
[
0.1
],
[
0.15
],
[
0.2
],
[
0.25
],
[
0.3
],
[
0.35
],
[
0.4
],
[
0.45
],
[
0.5
]
],
"hovertemplate": "A=%{x}
B=%{y}
SYSTEM TIME=%{customdata[0]}",
"legendgroup": "",
"marker": {
"color": "#2FAC74",
"size": 6,
"symbol": "circle"
},
"mode": "markers",
"name": "",
"orientation": "v",
"showlegend": false,
"type": "scatter",
"x": [
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],
"xaxis": "x",
"y": [
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36.9228125,
36.615265625,
36.47686953125,
36.4145912890625,
36.386566080078126,
36.37395473603516,
36.36827963121582
],
"yaxis": "y"
}
],
"layout": {
"annotations": [
{
"arrowcolor": "#b0b0b0",
"arrowhead": 0,
"ax": 0,
"ay": 20,
"bordercolor": "#c7c7c7",
"font": {
"color": "grey",
"size": 10
},
"showarrow": true,
"text": "t=0.0",
"x": 10,
"y": 50
},
{
"arrowcolor": "#b0b0b0",
"arrowhead": 0,
"ax": 16,
"ay": 28,
"bordercolor": "#c7c7c7",
"font": {
"color": "grey",
"size": 10
},
"showarrow": true,
"text": "0.05",
"x": 12.5,
"y": 42.5
},
{
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"arrowhead": 0,
"ax": 32,
"ay": 36,
"bordercolor": "#c7c7c7",
"font": {
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"size": 10
},
"showarrow": true,
"text": "0.1",
"x": 13.625,
"y": 39.125
},
{
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"arrowhead": 0,
"ax": 48,
"ay": 44,
"bordercolor": "#c7c7c7",
"font": {
"color": "grey",
"size": 10
},
"showarrow": true,
"text": "0.15",
"x": 14.13125,
"y": 37.60625
},
{
"arrowcolor": "#b0b0b0",
"arrowhead": 0,
"ax": 64,
"ay": 52,
"bordercolor": "#c7c7c7",
"font": {
"color": "grey",
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},
"showarrow": true,
"text": "0.2",
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},
{
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"ax": 96,
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"bordercolor": "#c7c7c7",
"font": {
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"size": 10
},
"showarrow": true,
"text": "0.3",
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"y": 36.47686953125
},
{
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Combine the two above plots, while using the layout of fig1 (which includes the title and annotations)\n",
"all_fig = go.Figure(data=fig0.data + fig1.data, layout = fig1.layout)\n",
"all_fig.show()"
]
},
{
"cell_type": "markdown",
"id": "4fe369cf-d2c0-454c-a3f9-9794008be8d8",
"metadata": {},
"source": [
"#### Note how the trajectory is progressively slowing down towards the dynamical system's \"attractor\" (equilibrium state of the reaction)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7f982020",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}